prithivMLmods/Llama-3.1-8B-Open-SFT is an 8 billion parameter language model fine-tuned from meta-llama/Llama-3.1-8B-Instruct. It leverages Supervised Fine-Tuning (SFT) on the O1-OPEN/OpenO1-SFT dataset to enhance performance in context-sensitive and instruction-following tasks. This model excels at advanced text generation, conversational AI, question answering, and Chain-of-Thought (CoT) reasoning, supporting a 32768 token context length. Its sharded architecture ensures efficient loading for various NLP applications.
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prithivMLmods/Llama-3.1-8B-Open-SFTMost commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.